Damage Detection of Irregular Plates and Regular Dams by Wavelet Transform Combined Adoptive Neuro Fuzzy Inference System

This paper presents a technique for irregular plate and regular dam damage detection based on combination of wavelet with adoptive neuro fuzzy inference system (ANFIS). Many damage detection methods need response of structures (such as the displacements, stresses or mode shapes) before and after damage, but this method only requires response of structures after damage, otherwise many damage detection methods study regular plate but this method also studies irregular plate. First, the structure (irregular plate or regular dam) is modelled by using ANSYS software, the model is analysed and structure’s responses with damage are obtained by finite element approach. Second, the responses at the finite element points with regular distances are obtained by using ANFIS. The damage zone is represented as the elements with reduced elasticity modules. Then these responses of structures are analysed with 2D wavelet transform. It is shown that matrix detail coefficients of 2D wavelet transform can specified the damage zone of plates and regular dams by perturbation in the damaged area

Commensurate 4a04a_0 period Charge Density Modulations throughout the Bi2Sr2CaCu2O8+xBi_2Sr_2CaCu_2O_{8+x} Pseudogap Regime

Theories based upon strong real space (r-space) electron electron interactions have long predicted that unidirectional charge density modulations (CDM) with four unit cell (4$a_0$) periodicity should occur in the hole doped cuprate Mott insulator (MI). Experimentally, however, increasing the hole density p is reported to cause the conventionally defined wavevector $Q_A$ of the CDM to evolve continuously as if driven primarily by momentum space (k-space) effects. Here we introduce phase resolved electronic structure visualization for determination of the cuprate CDM wavevector. Remarkably, this new technique reveals a virtually doping independent locking of the local CDM wavevector at $|Q_0|=2\pi/4a_0$ throughout the underdoped phase diagram of the canonical cuprate $Bi_2Sr_2CaCu_2O_8$. These observations have significant fundamental consequences because they are orthogonal to a k-space (Fermi surface) based picture of the cuprate CDM but are consistent with strong coupling r-space based theories. Our findings imply that it is the latter that provide the intrinsic organizational principle for the cuprate CDM state

Machine Learning in Electronic Quantum Matter Imaging Experiments

Essentials of the scientific discovery process have remained largely unchanged for centuries: systematic human observation of natural phenomena is used to form hypotheses that, when validated through experimentation, are generalized into established scientific theory. Today, however, we face major challenges because automated instrumentation and large-scale data acquisition are generating data sets of such volume and complexity as to defy human analysis. Radically different scientific approaches are needed, with machine learning (ML) showing great promise, not least for materials science research. Hence, given recent advances in ML analysis of synthetic data representing electronic quantum matter (EQM), the next challenge is for ML to engage equivalently with experimental data. For example, atomic-scale visualization of EQM yields arrays of complex electronic structure images, that frequently elude effective analyses. Here we report development and training of an array of artificial neural networks (ANN) designed to recognize different types of hypothesized order hidden in EQM image-arrays. These ANNs are used to analyze an experimentally-derived EQM image archive from carrier-doped cuprate Mott insulators. Throughout these noisy and complex data, the ANNs discover the existence of a lattice-commensurate, four-unit-cell periodic, translational-symmetry-breaking EQM state. Further, the ANNs find these phenomena to be unidirectional, revealing a coincident nematic EQM state. Strong-coupling theories of electronic liquid crystals are congruent with all these observations.Comment: 44 pages, 15 figure

Evidence for composite nature of quasiparticles in the 2D t-J model

It is shown that the dynamics of a single hole in a quantum antiferromagnet (described by the t--J model) can be simply understood in terms of a composite quasiparticle. This description provides naturally two different energy scales t and J corresponding to the inverse masses of the charge (holon) and spin (spinon) elementary excitations respectively. This picture is consistent with the exact results obtained on small clusters for the single hole spectral function and optical conductivity providing that one assumes the existence of a string-like force of magnitude J between the holon and the spinon. Then the hole quasiparticle can be interpreted as a bound state of its two constituents.Comment: 5 pages (revtex), 6 figures uuencoded, (Submitted to Nuclear Physics B

EPAS1 (Endothelial PAS Domain Protein 1)

Review on EPAS1, with data on DNA/RNA, on the protein encoded and where the gene is implicated